Bibliographic record
Abstract
OBJECTIVE: To review the efficacy and safety of vasopressin in cardiac arrest. DATA SOURCES: MEDLINE, EMBASE, and PubMed were searched (all to June 2005) for full-text English-language publications describing trials in humans. Search terms were vasopressin, epinephrine, adrenaline, heart arrest, cardiac arrest, and clinical trial. STUDY SELECTION AND DATA EXTRACTION: Prospective, randomized, controlled trials that evaluated efficacy or safety endpoints of vasopressin in the management of cardiac arrest were included. Efficacy outcomes included return of spontaneous circulation, successful resuscitation, survival to hospital admission, 24-hour survival, and survival to hospital discharge. Safety outcomes were as defined by each trial. DATA SYNTHESIS: Three prospective trials were identified and included in this review. Vasopressin does not appear to offer any therapeutic advantage compared with epinephrine in the treatment of both in-hospital and out-of-hospital cardiac arrest, regardless of the presenting arrest rhythm. Although there is a suggestion that vasopressin may be effective in treatment of asystole, the evidence for this arises from a subgroup analysis that should be viewed as hypothesis generating. There are limited data describing the safety of vasopressin in cardiac arrest. CONCLUSIONS: The current evidence for the use of vasopressin in cardiac arrest is indeterminate. Given the similarly equivocal evidence of efficacy for epinephrine, either drug could be considered the first-line agent in cardiac arrest. Placebo-controlled studies with appropriate statistical power are warranted to evaluate meaningful clinical outcomes, such as survival to hospital discharge. Further evaluation of the role of vasopressin in asystolic cardiac arrest and its use in combination with epinephrine is also justified.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".